Co-optimization of configuration and operation for distributed multi-energy system considering different optimization objectives and operation strategies

This study constructs a distributed multi-energy system (DMES) more suitable for development in the cities, which introduces renewable energy and energy storage technologies. Moreover, a novel multi-objective co-optimization framework for configuration and operation is proposed to address the design complexities of DMES. In the modeling process, the output and efficiency of the equipment vary with the load rate considered. In the solution process, the Pareto solution with three objectives (exergy, environment and economy) is obtained by an improved non-dominated sorting genetic algorithm-II (NSGA-II) using the maximum rectangular method, and then the trade-off solution is recognized by the entropy weight method. Finally, the impact of different objectives, operation strategies and system components on the system design is further explored. A hotel in Xi'an is selected as an illustrative example. The results prove that the improved NSGA-II can obtain a more uniform Pareto frontier. Furthermore, the capacity of renewable energy devices is identical for diverse operation strategies or optimization objectives. Compared to the two-objective optimization, the three-objective optimization reduces emissions by 28.86% but reduces energy efficiency by 1.51% and increases costs by 5.92%. Compared to the following thermal load strategy, the following electric load strategy reduces emissions by 27.96%, while increases energy efficiency and costs by 0.84% and 6.2%. Additionally, renewable energy sources and energy storage technologies, especially wind turbines, have a significant impact on the energy supply system of sustainable urban development.